Looking for advice on developing a MMM: Should I use Robyn or PyMC?

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Stan pystan bayesian-regression constrained-regression marketing-mix-modeling

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  • mmm_stan

    Python/STAN Implementation of Multiplicative Marketing Mix Model, with deep dive into Adstock (carry-over effect), ROAS, and mROAS

    • Question: Which Rabbit Hole to fall into? So far, it seems the best solution is either Robyn (most visualizations, lots of support / courses, can be automated on Google Cloud Platform, but uses R and apparently can't forecast), or PyMC (which uses Markov Chain Monte Carlo (MCMC). Additionally, there are some good github projects (MMM_STAN) that use Pystan (that use a domain specific C++ syntax to specify the model and data). Or, should I just use PyMC (in my native python) and then adapt to Robyn once I understand the basics? Does anyone have any thoughts or opinions?

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    Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.

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